A digital monitoring system and method for design data applied to intelligent buildings

Abstract

This invention discloses a digital monitoring system and method for design data in intelligent buildings, relating to the field of building area monitoring technology. The system includes: a design data processing unit, a data analysis module, and an intelligent building area monitoring module. The design data processing unit collects design drawings used in intelligent buildings, extracts information on each area within the building and the connecting channels between areas from the design drawings, and constructs a building area connectivity map. The data analysis module calculates the area congestion of each area node and the passage cost to the building exit in real time, determining the number of people to be transferred between area nodes. The intelligent building area monitoring module monitors the distribution of people in each area node in real time, determines whether each area node can accommodate the transfer of people, and guides the people in each area node in the building based on the iterative calculation results of the number of people that each area node can absorb.

Description

Technical Field

[0001] This invention relates to the field of building area monitoring technology, specifically a digital monitoring system and method for design data of intelligent buildings. Background Technology

[0002] In modern intelligent buildings, the evacuation management of high-density crowds after large gatherings and in the event of sudden disasters is an essential function.

[0003] In current building crowd evacuation management, common practices include placing fixed safety passage signs or setting up crowd control personnel at key road junctions inside buildings. These practices are mostly based on fixed evacuation routes for crowd distribution and lack consideration for the congestion levels in different areas of intelligent buildings and the evacuation costs from exits. Therefore, in actual operation, due to the different passage efficiency of different passages, crowd congestion often occurs in some small passages and small areas, resulting in uneven crowd evacuation. This greatly increases the probability of dangerous events such as stampedes and reduces the actual evacuation efficiency.

[0004] Therefore, there is a need for a digital monitoring system and method for design data in smart buildings to enable real-time monitoring of evacuated people, optimize evacuation efficiency, and improve evacuation safety. Summary of the Invention

[0005] The purpose of this invention is to provide a digital monitoring system and method for design data in intelligent buildings, in order to solve the problems raised in the prior art.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A method for digitally monitoring design data in intelligent buildings, comprising the following steps:

[0008] Step S100: Obtain intelligent building design data, divide and label the various areas within the building and the passageways between the areas, and construct a building area connectivity map; the intelligent building design data refers to the labeled data in the spatial design drawings of each area in the intelligent building;

[0009] Step S200: Obtain images of the distribution of people in each area of ​​the intelligent building, identify the number of people in each area, and calculate the congestion of each area node based on the building area connectivity graph.

[0010] Step S300: Based on the building area connectivity graph, calculate the passage cost of each area node and analyze the comprehensive passage cost of each area node reaching the building exit through each path.

[0011] Step S400: Based on the congestion level of each regional node and the comprehensive passage cost to the exit of the smart building, determine the number of people to be transferred between adjacent regions, and iteratively guide the people in each region of the smart building.

[0012] In the above technical solution, step S100 is divided into the following steps:

[0013] Step S101: Obtain the design drawings used in the intelligent building, and extract information on each area within the building and the connection channels between each area from the design drawings;

[0014] Step S102: Treat each region as a region node of the current smart building, and treat the connecting channels between regions as connecting lines between the region nodes of the current smart building to construct a building region connectivity graph;

[0015] When constructing a building area connectivity map, the area of ​​each area in the area information is used as the weight of the corresponding area node, and the maximum passage speed of the connecting channels between each area in the information of connecting channels between each area is used as the weight of the connecting line between area nodes. By analyzing the intelligent building design data to construct the building area connectivity map, the rationality of the transfer strategy can be effectively improved when monitoring the transfer of people in each area of ​​the building.

[0016] In the above technical solution, step S200 includes the following:

[0017] Image sensors are installed in various areas of the intelligent building to acquire images of the distribution of people in each area node, count the real-time number of people in each area node, and calculate the area congestion degree of each area node; for any area node a, according to the formula:

[0018]

[0019] Among them, C a Let N be the congestion level of region node a. a S represents the real-time number of people in region node a. a The weight of region node a;

[0020] Set an upper limit threshold C′ for regional congestion, and normalize the regional congestion of each node. The normalization formula is as follows:

[0021]

[0022] Among them, C′ a Let C′ be the normalized congestion degree of node a in region; when C′ a When C' > 1, C' a The value is corrected to 1;

[0023] By calculating and analyzing the congestion level of each area, the distribution of people in each area of ​​the building is reflected, which provides a scientific data basis for the population transfer strategy between areas, ensures the spatial rationality and safety of the population during actual evacuation and transfer, and reduces the safety risks during population evacuation.

[0024] In the above technical solution, step S300 includes the following:

[0025] Obtain the plan view of each area node in the building area connectivity graph. Based on the orientation of the connecting channels between each area node and adjacent area nodes, measure the travel distance through each area node. Combine the weight of the connecting lines between each area node to calculate the comprehensive travel cost of each path from area node a to the smart building exit.

[0026] For any path p, according to the formula:

[0027]

[0028] Where Cost(a, p) is the total travel cost from region node a to the smart building exit via path p, i is the region node number traversed by path p, and N is the total cost. p Let $p$ be the number of nodes in the region through which path $p$, and $Cost(i)$ be the travel cost to node $i$ in the region. i Let k be the travel distance of node i in the region traversed by path p. v v is the inter-regional travel coefficient. i C' represents the weight of the connection line between region node i and the next region node, where c1 and c2 are positive constant parameters. i The normalized congestion level of region node i is used. By combining the distance to the exit, regional congestion level, and passage speed of each region, the passage cost of different paths is analyzed. This reflects the impact of high congestion, narrow passages, and distance from the exit on the actual evacuation efficiency during the evacuation of high-density populations, and provides a relatively reliable data foundation for subsequent population transfer and evacuation strategies.

[0029] In the above technical solution, step S400 is divided into the following steps:

[0030] Step S401: Use a path planning algorithm to analyze the path with the minimum comprehensive passage cost from each regional node to the exit of the smart building;

[0031] Step S402: Starting from the regional node adjacent to the exit, traverse forward along each path, calculate the population transfer weight between adjacent regional nodes in each path and the population transfer capacity of each regional node, and determine the number of people transferred between each regional node.

[0032] Step S403: Based on the changes in the number of people in each area of ​​the smart building, iteratively guide the movement routes of people in each area.

[0033] In the above technical solution, the method for calculating the number of people transferred between adjacent regional nodes in each path in step S402 is as follows:

[0034] Extract the path information with the minimum comprehensive passage cost from all regional nodes to the smart building exit. For any regional node n, filter all paths passing through regional node n. For any filtered path, calculate the population transfer weight from the previous adjacent regional node to regional node n, according to the formula:

[0035]

[0036] Among them, w n-1 Cost(n-1, p) represents the population transfer weight from the previous neighboring region node of the current path region node n to region node n. n-1 ) represents the path p that the region node n-1 passes through. n-1 The overall cost of accessing the smart building exit;

[0037] Starting from the region node adjacent to the exit, traverse forward along each path. For any region node n, filter all paths involving region node n, and obtain the crowd transfer weights of all preceding adjacent region nodes of region node n in the filtered paths, according to the formula: The weights of the population transfer at each node are weighted and scaled.

[0038] Obtain the preset upper limit threshold C′ for regional congestion according to the formula: Calculate the population transfer capacity N′ of node n in the region. n ; where C′ n Let N be the normalized congestion degree of region node n. n Let C' be the real-time number of people in region node n; when C′ n When >C′, N′ n Corrected to 0;

[0039] Then, multiply the population transfer weight of each of the previous adjacent regional nodes of regional node n by the population transfer capacity of regional node n to obtain the number of people transferred from each of the previous adjacent regional nodes to regional node n.

[0040] By weighting the distribution of people in different regions, we can ensure a balanced distribution of people in different regions during evacuation. At the same time, by combining the real-time travel costs of each region, we can ensure the stability of travel during the transfer and distribution of people in each region and improve the actual efficiency of population transfer.

[0041] In the above technical solution, the method for iteratively guiding the movement routes of people in each area in step S403 is as follows:

[0042] Set a threshold for the proportion of people transferred, and deduce the threshold for the number of people transferred in each region based on the regional congestion calculation method.

[0043] When the crowd begins to move, calculate the congestion level and crowd transfer capacity of each regional node, determine the number of people to be transferred between each regional node, and guide the people who are closer to the inter-regional connection channel to move.

[0044] During the crowd transfer process, if the crowd congestion of any area node reaches the upper limit threshold of the area congestion, the area node is monitored. If the crowd transfer capacity of the area node is greater than the crowd transfer quantity threshold, it is determined that the area node can accommodate crowd transfer. The above method is used to iteratively calculate the number of crowd transfers that the area node can absorb, and crowd guidance is carried out.

[0045] If the population transfer capacity of the region is greater than the number of people that the region node can absorb from all the preceding region nodes in the involved path, then all the people in the preceding region nodes will be transferred.

[0046] By monitoring the crowd in real time and triggering iterative calculations for crowd transfer and allocation based on the threshold of the crowd transfer ratio, the system ensures the real-time nature of actual operations while avoiding frequent algorithm calculations, thereby improving the overall efficiency of the system and ensuring the timeliness of crowd evacuation guidance.

[0047] The above-described technical solution provides a digital monitoring method for design data in intelligent buildings, and a digital monitoring system for design data in intelligent buildings, comprising: a design data processing unit, a data analysis module, and an intelligent building area monitoring module.

[0048] The design data processing unit is used to collect the design drawings used in the intelligent building, extract information on each area within the building and the connecting channels between areas from the design drawings, and construct a building area connectivity map; the data analysis module calculates the area congestion of each area node and the passage cost to reach the building exit in real time, and determines the number of people to be transferred between area nodes; the intelligent building area monitoring module is used to monitor the distribution of people in each area node in real time, determine whether each area node can accommodate the transfer of people, and guide the people in each area node in the building based on the iterative calculation results of the number of people that each area node can absorb.

[0049] In the above technical solution, the data analysis module includes: a regional congestion calculation unit, a traffic cost analysis unit, and a transfer path planning unit;

[0050] The regional congestion calculation unit calculates the regional congestion data of each regional node based on the number of people in each region; the passage cost analysis unit is used to analyze the passage cost of each regional node in the intelligent building through which people transfer; the transfer path planning unit is used to calculate the comprehensive passage cost of people transferring from each region to the intelligent building exit, and plan the path with the minimum comprehensive passage cost of people transferring from each region.

[0051] In the above technical solution, the intelligent building area monitoring module includes: an area monitoring unit, a crowd transfer decision unit, and a crowd transfer guidance unit;

[0052] The regional monitoring unit is used to monitor the distribution of people in each area of ​​the intelligent building and identify the number of people in each area; the crowd transfer decision unit is used to analyze the crowd transfer weight of each regional node transferring people to the next regional node along the personnel transfer path, simultaneously calculate the crowd transfer capacity in each regional node, determine the number of people to be transferred in each regional node, and determine whether each regional node can accommodate crowd transfer; when the crowd transfer guidance unit determines that a regional node can accommodate crowd transfer, it sends a regional transfer signal to people who are closer to the inter-regional connection channel, and simultaneously sends the travel direction information of the target regional node.

[0053] Compared with the prior art, the present invention has the following beneficial effects:

[0054] This invention analyzes intelligent building design data to construct a building area connectivity map and monitors the distribution of people in each area of ​​the intelligent building in real time. It calculates the real-time distribution of people in each area, the congestion level, and the cost of reaching the exit, taking into account both area congestion and population evacuation efficiency. This achieves more precise population transfer allocation, improving the efficiency and safety of population evacuation. Furthermore, this invention uses real-time monitoring to identify changes in the number of people in each area and controls iterative calculations for population transfer, reducing redundant calculations while ensuring applicability in real-world, high-time-sensitivity scenarios. Finally, this invention determines the number of people to be transferred based on the congestion level of each area, ensuring a balance in congestion across areas, avoiding localized severe congestion, and mitigating safety risks during evacuation. Attached Figure Description

[0055] Figure 1 This is a flowchart of a digital monitoring method for design data applied to intelligent buildings according to the present invention;

[0056] Figure 2 This is an organizational structure diagram of a digital monitoring system for design data applied to intelligent buildings, as described in this invention. Detailed Implementation

[0057] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0058] Example: Please refer to Figure 1-Figure 2 This invention provides a technical solution.

[0059] like Figure 1 As shown, this invention provides a method for digital monitoring of design data applied to intelligent buildings, the method comprising the following steps:

[0060] Step S100: Obtain intelligent building design data, divide and label the various areas within the building and the passageways between the areas, and construct a building area connectivity map; the intelligent building design data refers to the labeled data in the spatial design drawings of each area in the intelligent building;

[0061] Step S200: Obtain images of the distribution of people in each area of ​​the intelligent building, identify the number of people in each area, and calculate the congestion of each area node based on the building area connectivity graph.

[0062] Step S300: Based on the building area connectivity graph, calculate the passage cost of each area node and analyze the comprehensive passage cost of each area node reaching the building exit through each path.

[0063] Step S400: Based on the congestion level of each regional node and the comprehensive passage cost to the exit of the smart building, determine the number of people to be transferred between adjacent regions, and iteratively guide the people in each region of the smart building.

[0064] In the above technical solution, step S100 is divided into the following steps:

[0065] Step S101: Obtain the design drawings used in the intelligent building, and extract information on each area within the building and the connection channels between each area from the design drawings;

[0066] Step S102: Treat each region as a region node of the current smart building, and treat the connecting channels between regions as connecting lines between the region nodes of the current smart building to construct a building region connectivity graph;

[0067] When constructing the building area connectivity map, the area of ​​each area in the area information is used as the weight of the corresponding area node, and the maximum passage speed of the inter-area connection channel in the inter-area connection channel information is used as the weight of the connection line between area nodes.

[0068] In practice, based on the building's internal construction drawings, the connection relationships between different areas within the building are analyzed. Based on the data in the construction drawings and the specifications of the connecting passages, the scale of each area and the maximum number of pedestrians passing between each area per unit time are calculated. In addition, to avoid complex calculations, the corridors can be divided into area nodes, and the area boundaries can be used as the connecting lines between areas.

[0069] When analyzing the efficiency of connecting passages, if there are periodic passage tools such as elevators, the average time for the elevator to travel to different floors and the maximum number of passengers the elevator can carry can be used to calculate the maximum passage speed of the elevator.

[0070] In the above technical solution, step S200 includes the following:

[0071] Image sensors are installed in various areas of the intelligent building to acquire images of the distribution of people in each area node, count the real-time number of people in each area node, and calculate the area congestion degree of each area node; for any area node a, according to the formula:

[0072]

[0073] Among them, C a Let N be the congestion level of region node a. a S represents the real-time number of people in region node a. a The weight of region node a;

[0074] Set an upper limit threshold C′ for regional congestion, and normalize the regional congestion of each node. The normalization formula is as follows:

[0075]

[0076] Among them, C′ a Let C′ be the normalized congestion degree of node a in region; when C′ a When >1, C′ a The value is corrected to 1.

[0077] In the above technical solution, step S300 includes the following:

[0078] Obtain the plan view of each area node in the building area connectivity graph. Based on the orientation of the connecting channels between each area node and adjacent area nodes, measure the travel distance through each area node. Combine the weight of the connecting lines between each area node to calculate the comprehensive travel cost of each path from area node a to the smart building exit.

[0079] For any path p, according to the formula:

[0080]

[0081] Where Cost(a, p) is the total travel cost from region node a to the smart building exit via path p, i is the region node number traversed by path p, and N is the total cost. p Let $p$ be the number of nodes in the region through which path $p$, and $Cost(i)$ be the travel cost to node $i$ in the region. i Let k be the travel distance of node i in the region traversed by path p. v v is the inter-regional travel coefficient. i C' represents the weight of the connection line between region node i and the next region node, where c1 and c2 are positive constant parameters. i Let i be the normalized congestion level of region node i;

[0082] In practice, considering that the farther the crowd is from the building exit, the higher the congestion of the area, and the lower the efficiency of the connecting passage between the areas, the longer the actual evacuation time will be, the more comprehensive the calculation of the passage cost for each area and route is made.

[0083] In the above technical solution, step S400 is divided into the following steps:

[0084] Step S401: Use a path planning algorithm to analyze the path with the minimum comprehensive passage cost from each regional node to the exit of the smart building;

[0085] Step S402: Starting from the regional node adjacent to the exit, traverse forward along each path, calculate the population transfer weight between adjacent regional nodes in each path and the population transfer capacity of each regional node, and determine the number of people transferred between each regional node.

[0086] Step S403: Based on the changes in the number of people in each area of ​​the smart building, iteratively guide the movement routes of people in each area.

[0087] In the above technical solution, the method for calculating the number of people transferred between adjacent regional nodes in each path in step S402 is as follows:

[0088] Extract the path information with the minimum comprehensive passage cost from all regional nodes to the smart building exit. For any regional node n, filter all paths passing through regional node n. For any filtered path, calculate the population transfer weight from the previous adjacent regional node to regional node n, according to the formula:

[0089]

[0090] Among them, w n-1 Cost(n-1, p) represents the population transfer weight from the previous neighboring region node of the current path region node n to region node n. n-1) represents the path p that the region node n-1 passes through. n-1 The overall cost of accessing the smart building exit;

[0091] Starting from the region node adjacent to the exit, traverse forward along each path. For any region node n, filter all paths involving region node n, and obtain the crowd transfer weights of all preceding adjacent region nodes of region node n in the filtered paths, according to the formula: The weights of the population transfer at each node are weighted and scaled.

[0092] Obtain the preset upper limit threshold C′ for regional congestion according to the formula: Calculate the population transfer capacity N′ of node n in the region. n ; where C′ n Let N be the normalized congestion degree of region node n. n Let C' be the real-time number of people in region node n; when C′ n When >C′, N′ n Corrected to 0;

[0093] Then, multiply the population transfer weight of each of the previous adjacent regional nodes of regional node n by the population transfer capacity of regional node n to obtain the number of people transferred from each of the previous adjacent regional nodes to regional node n.

[0094] In practice, after selecting a regional node, we analyze whether the path with the lowest overall travel cost among the other regional nodes passes through the current regional node. If it does, we then filter all the previous regional nodes of the current regional node in each path and calculate the population transfer weight.

[0095] In the above technical solution, the method for iteratively guiding the movement routes of people in each area in step S403 is as follows:

[0096] Set a threshold for the proportion of people transferred, and deduce the threshold for the number of people transferred in each region based on the regional congestion calculation method.

[0097] When the crowd begins to move, calculate the congestion level and crowd transfer capacity of each regional node, determine the number of people to be transferred between each regional node, and guide the people who are closer to the inter-regional connection channel to move.

[0098] During the crowd transfer process, if the crowd congestion of any area node reaches the upper limit threshold of the area congestion, the area node is monitored. If the crowd transfer capacity of the area node is greater than the crowd transfer quantity threshold, it is determined that the area node can accommodate crowd transfer. The above method is used to iteratively calculate the number of crowd transfers that the area node can absorb, and crowd guidance is carried out.

[0099] If the population transfer capacity of the region is greater than the number of people that the region node can absorb from all the preceding region nodes in the involved path, then all the people in the preceding region nodes will be transferred.

[0100] In practical implementation, during a single iteration, since the collected data is from the same time period, the flow of people in each area tends to converge towards the exit. Since different paths do not separate after the initial intersection point, there is no need to consider a scenario where a single area node is distributed divergently to multiple area nodes. Furthermore, due to real-time changes in the number of people in each area, the area congestion also changes. Therefore, the path with the minimum comprehensive passage cost for each area in real-time analysis is adaptively changed, guiding people from areas far from the exit towards the exit, avoiding the situation where a small number of people are assigned to areas far from the exit due to the proportional allocation calculation method. After guiding people from each area of ​​the building towards the exit, the number of people further transferring to the exit from each area is calculated based on the population transfer weight. The population transfer weight is calculated based on the passage cost to ensure that the time spent on population transfer in each area is relatively similar, further improving the efficiency of overall population transfer and evacuation supervision.

[0101] like Figure 2 The present invention also provides a digital monitoring system for design data of intelligent buildings, the system comprising: a design data processing unit, a data analysis module, and an intelligent building area monitoring module;

[0102] The design data processing unit is used to collect the design drawings used in the intelligent building, extract information on each area within the building and the connecting channels between areas from the design drawings, and construct a building area connectivity map; the data analysis module calculates the area congestion of each area node and the passage cost to reach the building exit in real time, and determines the number of people to be transferred between area nodes; the intelligent building area monitoring module is used to monitor the distribution of people in each area node in real time, determine whether each area node can accommodate the transfer of people, and guide the people in each area node in the building based on the iterative calculation results of the number of people that each area node can absorb.

[0103] In the above technical solution, the data analysis module includes: a regional congestion calculation unit, a traffic cost analysis unit, and a transfer path planning unit;

[0104] The regional congestion calculation unit calculates the regional congestion data of each regional node based on the number of people in each region; the passage cost analysis unit is used to analyze the passage cost of each regional node in the intelligent building through which people transfer; the transfer path planning unit is used to calculate the comprehensive passage cost of people transferring from each region to the intelligent building exit, and plan the path with the minimum comprehensive passage cost of people transferring from each region.

[0105] In the above technical solution, the intelligent building area monitoring module includes: an area monitoring unit, a crowd transfer decision unit, and a crowd transfer guidance unit;

[0106] The regional monitoring unit is used to monitor the distribution of people in each area of ​​the intelligent building and identify the number of people in each area; the crowd transfer decision unit is used to analyze the crowd transfer weight of each regional node transferring people to the next regional node along the personnel transfer path, simultaneously calculate the crowd transfer capacity in each regional node, determine the number of people to be transferred in each regional node, and determine whether each regional node can accommodate crowd transfer; when the crowd transfer guidance unit determines that a regional node can accommodate crowd transfer, it sends a regional transfer signal to people who are closer to the inter-regional connection channel, and simultaneously sends the travel direction information of the target regional node.

[0107] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A method for digitally monitoring design data applied to intelligent buildings, characterized in that... The method consists of the following steps: Step S100: Obtain intelligent building design data, divide and label the various areas within the building and the passageways between the areas, and construct a building area connectivity map; The intelligent building design data refers to the data marked on the spatial design drawings of each area in the intelligent building; Step S200: Obtain images of the distribution of people in each area of ​​the intelligent building, identify the number of people in each area, and calculate the congestion of each area node based on the building area connectivity graph. Step S300: Based on the building area connectivity graph, calculate the passage cost of each area node and analyze the comprehensive passage cost of each area node reaching the building exit through each path. Step S400: Based on the congestion level of each regional node and the comprehensive passage cost to the smart building exit, determine the number of people to be transferred between adjacent regions, and iteratively guide the people in each region of the smart building. Step S400 includes the following steps: Extract the path information with the minimum comprehensive passage cost from all regional nodes to the smart building exit. For any regional node n, filter all paths passing through regional node n. For any filtered path, calculate the population transfer weight from regional node n-1 to regional node n according to the formula: ； in, The transfer weights for people moving from region node n-1 in the current path to region node n. For region node n-1, the path through the node belongs to this node The overall cost of accessing the smart building exit; Starting from the region node adjacent to the exit, traverse forward along each path. For any region node n, filter all paths involving region node n, and obtain the crowd transfer weights of all preceding adjacent region nodes of region node n in the filtered paths, according to the formula: The weights of the population transfer at each node are weighted and scaled. Get the preset regional congestion limit threshold According to the formula: Calculate the population transfer capacity of node n in the region. ;in, Let n be the normalized congestion degree of the region node n. The real-time number of people in region node n; when At that time, Corrected to 0; Then, multiply the population transfer weight of each of the previous adjacent regional nodes of regional node n by the population transfer capacity of regional node n to obtain the number of people transferred from each of the previous adjacent regional nodes to regional node n. Set a threshold for the proportion of people transferred, and deduce the threshold for the number of people transferred in each region based on the regional congestion calculation method. When the crowd begins to move, calculate the congestion level and crowd transfer capacity of each regional node, determine the number of people to be transferred between each regional node, and guide the people who are closer to the inter-regional connection channel to move. During the crowd transfer process, if the crowd congestion of any area node reaches the upper limit threshold of the area congestion, the area node is monitored. If the crowd transfer capacity of the area node is greater than the crowd transfer quantity threshold, it is determined that the area node can accommodate crowd transfer. The above method is used to iteratively calculate the number of crowd transfers that the area node can absorb, and crowd guidance is carried out. If the population transfer capacity of the region is greater than the number of people that the region node can absorb from all the preceding region nodes in the involved path, then all the people in the preceding region nodes will be transferred.

2. The method for digital monitoring of design data applied to intelligent buildings according to claim 1, characterized in that, Step S100 consists of the following steps: Step S101: Obtain the design drawings used in the intelligent building, and extract information on each area within the building and the connection channels between each area from the design drawings; Step S102: Treat each region as a region node of the current smart building, and treat the connecting channels between regions as connecting lines between the region nodes of the current smart building to construct a building region connectivity graph; When constructing the connectivity map of building areas, the area of ​​each area in the area information is used as the weight of the corresponding area node, and the maximum passage speed of the connecting channel between each area in the connecting channel information between each area is used as the weight of the connecting line between area nodes.

3. The method for digital monitoring of design data applied to intelligent buildings according to claim 2, characterized in that, Step S200 includes the following: Image sensors are installed in various areas of the smart building to acquire images of the distribution of people in each area node. The real-time number of people in each area node is counted, and the area congestion degree of each area node is calculated according to the formula: For any area node a, ； in, The congestion level of region node a. This represents the real-time number of people in region node a. The weight of region node a; Set an upper limit threshold for regional congestion. The congestion level of each node in each region is normalized using the following formula: ； in, Let be the normalized congestion degree of region node a; when At that time, The value is corrected to 1.

4. The method for digital monitoring of design data applied to intelligent buildings according to claim 2, characterized in that, Step S300 includes the following: Obtain the plan view of each node in the building area connectivity graph. Based on the orientation of the connecting channels between each node and its adjacent nodes, measure the travel distance through each node. Combining the weights of the connecting lines between nodes, calculate the comprehensive travel cost of each path from node a to the smart building exit using the formula: For any path p, ； ； in, Let i be the total travel cost from region node a to the smart building exit via path p, where i is the region node number traversed by path p. Let p be the number of nodes in the region it passes through. Let i be the passage cost for region node i. Let be the travel distance of node i in the region traversed by path p. This is the inter-regional connectivity coefficient. Let be the weight of the connection line between region node i and the next region node. and For positive constant parameters, Let be the normalized congestion level of region node i.

5. A method for digital monitoring of design data applied to intelligent buildings according to claim 2, characterized in that, Step S400 consists of the following steps: Step S401: Use a path planning algorithm to analyze the path with the minimum comprehensive passage cost from each regional node to the exit of the smart building; Step S402: Starting from the regional node adjacent to the exit, traverse forward along each path, calculate the population transfer weight between adjacent regional nodes in each path and the population transfer capacity of each regional node, and determine the number of people transferred between each regional node. Step S403: Based on the changes in the number of people in each area of ​​the smart building, iteratively guide the movement routes of people in each area.

6. A digital monitoring system for design data in intelligent buildings, used to implement the digital monitoring method for design data in intelligent buildings as described in any one of claims 1-5, characterized in that, The system includes: a design data processing unit, a data analysis module, and an intelligent building area monitoring module; The design data processing unit is used to collect the design drawings used in the intelligent building, extract information on each area within the building and the connecting channels between areas from the design drawings, and construct a building area connectivity map; the data analysis module calculates the area congestion of each area node and the passage cost to reach the building exit in real time, and determines the number of people to be transferred between area nodes; the intelligent building area monitoring module is used to monitor the distribution of people in each area node in real time, determine whether each area node can accommodate the transfer of people, and guide the people in each area node in the building based on the iterative calculation results of the number of people that each area node can absorb.

7. A digital monitoring system for design data applied to intelligent buildings according to claim 6, characterized in that, The data analysis module includes: a regional congestion calculation unit, a traffic cost analysis unit, and a transfer path planning unit; The regional congestion calculation unit calculates the regional congestion data of each regional node based on the number of people in each region; the passage cost analysis unit is used to analyze the passage cost of each regional node in the intelligent building through which people transfer; the transfer path planning unit is used to calculate the comprehensive passage cost of people transferring from each region to the intelligent building exit, and plan the path with the minimum comprehensive passage cost of people transferring from each region.

8. A digital monitoring system for design data applied to intelligent buildings according to claim 6, characterized in that, The intelligent building area monitoring module includes: an area monitoring unit, a crowd relocation decision-making unit, and a crowd relocation guidance unit; The regional monitoring unit is used to monitor the distribution of people in each area of ​​the intelligent building and identify the number of people in each area; the crowd transfer decision unit is used to analyze the crowd transfer weight of each regional node transferring people to the next regional node along the personnel transfer path, simultaneously calculate the crowd transfer capacity in each regional node, determine the number of people to be transferred in each regional node, and determine whether each regional node can accommodate crowd transfer; when the crowd transfer guidance unit determines that a regional node can accommodate crowd transfer, it sends a regional transfer signal to people who are closer to the inter-regional connection channel, and simultaneously sends the travel direction information of the target regional node.

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